Energy-efficient multi-focus image fusion based on neighbor distance and morphology
To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, rel...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Liu, Caiping [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
|---|
| Schlagwörter: |
|---|
| Umfang: |
10 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment - Cheng, Cheng ELSEVIER, 2020, international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy, München |
|---|---|
| Übergeordnetes Werk: |
volume:127 ; year:2016 ; number:23 ; pages:11354-11363 ; extent:10 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.ijleo.2016.09.038 |
|---|
| Katalog-ID: |
ELV014686104 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | ELV014686104 | ||
| 003 | DE-627 | ||
| 005 | 20230625113747.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 180602s2016 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.ijleo.2016.09.038 |2 doi | |
| 028 | 5 | 2 | |a GBVA2016023000024.pica |
| 035 | |a (DE-627)ELV014686104 | ||
| 035 | |a (ELSEVIER)S0030-4026(16)31046-4 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | |a 620 | |
| 082 | 0 | 4 | |a 620 |q DE-600 |
| 082 | 0 | 4 | |a 333.7 |q VZ |
| 084 | |a 43.00 |2 bkl | ||
| 100 | 1 | |a Liu, Caiping |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| 264 | 1 | |c 2016transfer abstract | |
| 300 | |a 10 | ||
| 336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
| 337 | |a nicht spezifiziert |b z |2 rdamedia | ||
| 338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
| 520 | |a To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). | ||
| 520 | |a To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). | ||
| 650 | 7 | |a Neighbor distance |2 Elsevier | |
| 650 | 7 | |a Multi-focus image |2 Elsevier | |
| 650 | 7 | |a Energy-efficient |2 Elsevier | |
| 650 | 7 | |a Mathematical morphology |2 Elsevier | |
| 650 | 7 | |a Image fusion |2 Elsevier | |
| 700 | 1 | |a Long, Yahui |4 oth | |
| 700 | 1 | |a Mao, Jianxu |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |n Elsevier |a Cheng, Cheng ELSEVIER |t Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |d 2020 |d international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy |g München |w (DE-627)ELV004102533 |
| 773 | 1 | 8 | |g volume:127 |g year:2016 |g number:23 |g pages:11354-11363 |g extent:10 |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.ijleo.2016.09.038 |3 Volltext |
| 912 | |a GBV_USEFLAG_U | ||
| 912 | |a GBV_ELV | ||
| 912 | |a SYSFLAG_U | ||
| 912 | |a SSG-OLC-PHA | ||
| 912 | |a SSG-OPC-GGO | ||
| 936 | b | k | |a 43.00 |j Umweltforschung |j Umweltschutz: Allgemeines |q VZ |
| 951 | |a AR | ||
| 952 | |d 127 |j 2016 |e 23 |h 11354-11363 |g 10 | ||
| 953 | |2 045F |a 620 | ||
| author_variant |
c l cl |
|---|---|
| matchkey_str |
liucaipinglongyahuimaojianxu:2016----:nryfiinmliouiaeuinaeonihods |
| hierarchy_sort_str |
2016transfer abstract |
| bklnumber |
43.00 |
| publishDate |
2016 |
| allfields |
10.1016/j.ijleo.2016.09.038 doi GBVA2016023000024.pica (DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 DE-627 ger DE-627 rakwb eng 620 620 DE-600 333.7 VZ 43.00 bkl Liu, Caiping verfasserin aut Energy-efficient multi-focus image fusion based on neighbor distance and morphology 2016transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier Long, Yahui oth Mao, Jianxu oth Enthalten in Elsevier Cheng, Cheng ELSEVIER Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment 2020 international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy München (DE-627)ELV004102533 volume:127 year:2016 number:23 pages:11354-11363 extent:10 https://doi.org/10.1016/j.ijleo.2016.09.038 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 127 2016 23 11354-11363 10 045F 620 |
| spelling |
10.1016/j.ijleo.2016.09.038 doi GBVA2016023000024.pica (DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 DE-627 ger DE-627 rakwb eng 620 620 DE-600 333.7 VZ 43.00 bkl Liu, Caiping verfasserin aut Energy-efficient multi-focus image fusion based on neighbor distance and morphology 2016transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier Long, Yahui oth Mao, Jianxu oth Enthalten in Elsevier Cheng, Cheng ELSEVIER Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment 2020 international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy München (DE-627)ELV004102533 volume:127 year:2016 number:23 pages:11354-11363 extent:10 https://doi.org/10.1016/j.ijleo.2016.09.038 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 127 2016 23 11354-11363 10 045F 620 |
| allfields_unstemmed |
10.1016/j.ijleo.2016.09.038 doi GBVA2016023000024.pica (DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 DE-627 ger DE-627 rakwb eng 620 620 DE-600 333.7 VZ 43.00 bkl Liu, Caiping verfasserin aut Energy-efficient multi-focus image fusion based on neighbor distance and morphology 2016transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier Long, Yahui oth Mao, Jianxu oth Enthalten in Elsevier Cheng, Cheng ELSEVIER Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment 2020 international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy München (DE-627)ELV004102533 volume:127 year:2016 number:23 pages:11354-11363 extent:10 https://doi.org/10.1016/j.ijleo.2016.09.038 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 127 2016 23 11354-11363 10 045F 620 |
| allfieldsGer |
10.1016/j.ijleo.2016.09.038 doi GBVA2016023000024.pica (DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 DE-627 ger DE-627 rakwb eng 620 620 DE-600 333.7 VZ 43.00 bkl Liu, Caiping verfasserin aut Energy-efficient multi-focus image fusion based on neighbor distance and morphology 2016transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier Long, Yahui oth Mao, Jianxu oth Enthalten in Elsevier Cheng, Cheng ELSEVIER Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment 2020 international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy München (DE-627)ELV004102533 volume:127 year:2016 number:23 pages:11354-11363 extent:10 https://doi.org/10.1016/j.ijleo.2016.09.038 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 127 2016 23 11354-11363 10 045F 620 |
| allfieldsSound |
10.1016/j.ijleo.2016.09.038 doi GBVA2016023000024.pica (DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 DE-627 ger DE-627 rakwb eng 620 620 DE-600 333.7 VZ 43.00 bkl Liu, Caiping verfasserin aut Energy-efficient multi-focus image fusion based on neighbor distance and morphology 2016transfer abstract 10 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier Long, Yahui oth Mao, Jianxu oth Enthalten in Elsevier Cheng, Cheng ELSEVIER Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment 2020 international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy München (DE-627)ELV004102533 volume:127 year:2016 number:23 pages:11354-11363 extent:10 https://doi.org/10.1016/j.ijleo.2016.09.038 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO 43.00 Umweltforschung Umweltschutz: Allgemeines VZ AR 127 2016 23 11354-11363 10 045F 620 |
| language |
English |
| source |
Enthalten in Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment München volume:127 year:2016 number:23 pages:11354-11363 extent:10 |
| sourceStr |
Enthalten in Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment München volume:127 year:2016 number:23 pages:11354-11363 extent:10 |
| format_phy_str_mv |
Article |
| bklname |
Umweltforschung Umweltschutz: Allgemeines |
| institution |
findex.gbv.de |
| topic_facet |
Neighbor distance Multi-focus image Energy-efficient Mathematical morphology Image fusion |
| dewey-raw |
620 |
| isfreeaccess_bool |
false |
| container_title |
Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |
| authorswithroles_txt_mv |
Liu, Caiping @@aut@@ Long, Yahui @@oth@@ Mao, Jianxu @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
ELV004102533 |
| dewey-sort |
3620 |
| id |
ELV014686104 |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV014686104</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625113747.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ijleo.2016.09.038</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016023000024.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV014686104</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0030-4026(16)31046-4</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">333.7</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">43.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Caiping</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Energy-efficient multi-focus image fusion based on neighbor distance and morphology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">10</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT).</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neighbor distance</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-focus image</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Energy-efficient</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Mathematical morphology</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Image fusion</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Long, Yahui</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mao, Jianxu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Cheng, Cheng ELSEVIER</subfield><subfield code="t">Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment</subfield><subfield code="d">2020</subfield><subfield code="d">international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy</subfield><subfield code="g">München</subfield><subfield code="w">(DE-627)ELV004102533</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:127</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:23</subfield><subfield code="g">pages:11354-11363</subfield><subfield code="g">extent:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ijleo.2016.09.038</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-GGO</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">43.00</subfield><subfield code="j">Umweltforschung</subfield><subfield code="j">Umweltschutz: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">127</subfield><subfield code="j">2016</subfield><subfield code="e">23</subfield><subfield code="h">11354-11363</subfield><subfield code="g">10</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">620</subfield></datafield></record></collection>
|
| author |
Liu, Caiping |
| spellingShingle |
Liu, Caiping ddc 620 ddc 333.7 bkl 43.00 Elsevier Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| authorStr |
Liu, Caiping |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV004102533 |
| format |
electronic Article |
| dewey-ones |
620 - Engineering & allied operations 333 - Economics of land & energy |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
elsevier |
| remote_str |
true |
| illustrated |
Not Illustrated |
| topic_title |
620 620 DE-600 333.7 VZ 43.00 bkl Energy-efficient multi-focus image fusion based on neighbor distance and morphology Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion Elsevier |
| topic |
ddc 620 ddc 333.7 bkl 43.00 Elsevier Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion |
| topic_unstemmed |
ddc 620 ddc 333.7 bkl 43.00 Elsevier Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion |
| topic_browse |
ddc 620 ddc 333.7 bkl 43.00 Elsevier Neighbor distance Elsevier Multi-focus image Elsevier Energy-efficient Elsevier Mathematical morphology Elsevier Image fusion |
| format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
zu |
| author2_variant |
y l yl j m jm |
| hierarchy_parent_title |
Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |
| hierarchy_parent_id |
ELV004102533 |
| dewey-tens |
620 - Engineering 330 - Economics |
| hierarchy_top_title |
Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)ELV004102533 |
| title |
Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| ctrlnum |
(DE-627)ELV014686104 (ELSEVIER)S0030-4026(16)31046-4 |
| title_full |
Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| author_sort |
Liu, Caiping |
| journal |
Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |
| journalStr |
Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology 300 - Social sciences |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
zzz |
| container_start_page |
11354 |
| author_browse |
Liu, Caiping |
| container_volume |
127 |
| physical |
10 |
| class |
620 620 DE-600 333.7 VZ 43.00 bkl |
| format_se |
Elektronische Aufsätze |
| author-letter |
Liu, Caiping |
| doi_str_mv |
10.1016/j.ijleo.2016.09.038 |
| dewey-full |
620 333.7 |
| title_sort |
energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| title_auth |
Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| abstract |
To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). |
| abstractGer |
To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). |
| abstract_unstemmed |
To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT). |
| collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-GGO |
| container_issue |
23 |
| title_short |
Energy-efficient multi-focus image fusion based on neighbor distance and morphology |
| url |
https://doi.org/10.1016/j.ijleo.2016.09.038 |
| remote_bool |
true |
| author2 |
Long, Yahui Mao, Jianxu |
| author2Str |
Long, Yahui Mao, Jianxu |
| ppnlink |
ELV004102533 |
| mediatype_str_mv |
z |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth oth |
| doi_str |
10.1016/j.ijleo.2016.09.038 |
| up_date |
2024-07-06T22:09:14.370Z |
| _version_ |
1803869229544374272 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV014686104</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230625113747.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180602s2016 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.ijleo.2016.09.038</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBVA2016023000024.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV014686104</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0030-4026(16)31046-4</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">620</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">333.7</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">43.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liu, Caiping</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Energy-efficient multi-focus image fusion based on neighbor distance and morphology</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">10</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT).</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">To solve the problem of the discontinuity of focus region in fused image based on traditional multi-scale analysis and reduce the complexity of fusion method, an energy-efficient multi-focus image fusion algorithm based on multi-scale neighbor distance analysis and morphology is proposed. First, relative to traditional multi-scale analysis, multi-scale neighbor distance analysis can also effectively extract the details of images. The lowpass subband coefficient and highpass subband coefficient are produced based on it, and, then, all of coefficients are divided into blocks with the same size. Second, a coefficient in the highpass subband is seriously related to corresponding one in the lowpass subband. Based on this, block is compared with pair-based scheme in transform domain by using some new fusion rules. As a result, the focused region of source images are determined, and the initial map is acquired. The mathematical morphology is used for post-processing. Finally, the fused image is obtained with the guidance of the decision map. The experimental results demonstrate that the proposed method is effective and can provide better performance in both fusing multi-focus image and the computational complexity than some state-of-art multi-scale analysis-based methods, such as the nonsubsampled contourlet transform (NSCT), contourlet transform, wavelet transform and lifting stationary wavelet transform (LSWT).</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neighbor distance</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Multi-focus image</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Energy-efficient</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Mathematical morphology</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Image fusion</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Long, Yahui</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mao, Jianxu</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Cheng, Cheng ELSEVIER</subfield><subfield code="t">Tracking variation of fluorescent dissolved organic matter during full-scale printing and dyeing wastewater treatment</subfield><subfield code="d">2020</subfield><subfield code="d">international journal for light and electron optics : official journal of the German Society of Applied Optics and the German Society of Electron Microscopy</subfield><subfield code="g">München</subfield><subfield code="w">(DE-627)ELV004102533</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:127</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:23</subfield><subfield code="g">pages:11354-11363</subfield><subfield code="g">extent:10</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.ijleo.2016.09.038</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-PHA</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-GGO</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">43.00</subfield><subfield code="j">Umweltforschung</subfield><subfield code="j">Umweltschutz: Allgemeines</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">127</subfield><subfield code="j">2016</subfield><subfield code="e">23</subfield><subfield code="h">11354-11363</subfield><subfield code="g">10</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">620</subfield></datafield></record></collection>
|
| score |
7.402915 |